PROFESSOR DR. HONG-MEI CHEN Full Professor of IT Management Shidler College of Business (SCB) University of Hawaii at Manoa Honolulu, USA Former Associate Dean of SCB
III. Big data management Business-IT Alignment Service Engineering CURRENT RESEARCH PROGRAM I. Ultra Large-scale Green IS Metropolis Model System of Systems II. Social CRM Service Dominant Logic (SDL) Service Ecosystems
RELATED PUBLICATIONS I. Ultra Large-scale Green IS Hong-Mei Chen and Rick Kazman. Architecting for Ultra Large Scale Green IS, Proceedings of GREENS, ICSE 2012. Rick Kazman and Hong-Mei Chen. "The Metropolis Model: A New Logic for the Development of Crowdsourced Systems," Communications of the ACM, Volume 52, Issue 7 (July 2009), pp. 76-84. II. Social CRM Hong-Mei Chen and Stephen L. Vargo. Rethinking Social CRM Design: A Service Dominant Logic Perspective, In Handbook on e-business strategic management, Springer, 2014. Hong-Mei Chen and Stephen L. Vargo, Service -Oriented Challenges for Design Science: Charting the E -volution, Pacific Asian Journal of the Association of Information Systems, Vol. 2 No. 1, March 2010, pp.1-15. III. Big Data Management Hong-Mei Chen, Rick Kazman, and Opal Perry. From Software Architecture Analysis to Service Engineering: An Empirical Study of Methodology Development for Enterprise SOA Implementation. IEEE Transaction on Services Computing, April-June 2010 (vol. 3 no. 2), pp. 145-160.
I. ULTRA LARGE-SCALE GREEN IS Case Study: USA Smart Grid Demand Respond System Project Sponsor: USA Department of Energy Objective: To help individual Utility Company with architecture design in the Smart Grid context Result: ULTRA-GREEN Framework and ECO-ARCH Method optimizing Triple-Bottom-Line Current tasks: Seeking companies to validate & refine the method for other ULS-Green IS or Smart Grids in other countries
ULTRA-GREEN design framework (Chen & Kazman 2012)
ECO-ARCH Method (Chen & Kazman 2012)
II. SOCIAL SCRM Objective: Strategic roadmap for companies to develop Social CRM systems successfully Results: Service-Dominant Logic (SDL) implied SCRM System Design Framework Current tasks Seeking Companies for collaborative development of appropriate SCRM many-to-many interaction model, success metrics and design methodology for service eco-system
SDL Informed SCRM Design (Chen & Vargo 2014) S-D logic FP FP 6: The customer is always a co-creator of value. FP 7: The enterprise cannot deliver value, but only offer value propositions. FP 8: A service-centered view is inherently customer oriented and relational. FP 9: All social and economic actors are resource integrators. FP 10: Value is always uniquely and phenomenologically determined by the beneficiary. Traditional ECRM Design one to one design; customer as external entities; strict system boundary; static view of users/customers and interaction process; single-view of customer, focus on firm s processes; requirements relatively welldefined. value presumed by firms; firm internal process integration; value configuration from firm s resources. treat repeat patronage as relationship; shorter term economic benefit/value/profitability measurement firm competency and resources; relative fixed design outcome or service innovation metrics: value assumed predetermined (disconfirmationbased) S-D informed ECRM (or SCRM) Design many-to-many design; include customer competencies and networks; fluid system boundary; dynamic service adaptation for customers; focus both firms and customers processes and others; analysis of the entire customer network; shared information among customers, firms and networks; some requirements unknown. value in context; internal & external process integration in the customer s context; dynamic value configuration with customers network and supplier chains; firm propositions as part of customer s value creation. treat relationship as core process in value creation. longer term customer advocacy measurement; customers and their networks are co-creators of the brand including both firm s and customer s competencies and resources for value co-creation; dynamic integration for personalization; end-to-end process integration; capability of emergent outcome or unexpected service innovation metrics for emergent concept of (co-created) value; value measurement needs to be capture intangible, experiential, contextual, meaning-laden quality of interaction (dynamic) at each touch point; people, process, product (service) are integrated for each interaction
SCRM Research Model (Chen 2012) Platform preference motivation Privacy concerns expectation Platform attributes Social customers Easy of participation Many to Many Interaction Incentive for participation Advocacy collaboration Mechanisms Message reach Level of influence Propensity to contribute in public Culture Innovation Share of voice Co-created value Profitability
Service Ecosystems: the Outcome and Context of Resource Integration & Service Exchange Macro Meso Micro Institutions Resource Integrators
III. BIG DATA MANAGEMENT Objective: Architecture-focused Business-IT Alignment Approach for Big Data System (BDS) Design Foundations: 1) BITAM (Chen, Kazman & Garg,2005), with Fedex 2) BITAM-SOA (Chen, Kazman & Perry, 2010), with Wells Fargo Bank Results-in-Progress: BITAM-BDM framework and BDS design method including semi-automated big data technology road mapping, technology selection trade-off analysis Current tasks Seeking Companies for collaborative development and validation of the method
1) Business Model layer: drivers, strategies, revenue streams, investments, constraints, regulations, policy 2) Business Architecture layer: applications, business processes, workflow, data flow, organization, skills Customer-Centric Value Proposition Cost Benefits External business services Business Processes External application services Application Portfolio Stakeholder Perspective Financial Perspective Activity Perspective Service Innovation Social Dimension Technical Dimension SOA 3) IT Architecture layer: hardware, software, networks, components, interfaces, platforms, standards External infrastructure services IT Infrastructure Resource Perspective Big data Clouds 3-Layer BITAM Architecture Enterprise Architecture BPM + IT Service Management BITAM-BDM (Business-IT Alignment Model for Big Data Management) Framework 14
CONCLUSIONS Cross-disciplinary, Design Science and Service Engineering approach Adopt new design thinking Address emerging wicked problems (unordered, complex problems) in Information Systems domain Employing qualitative and quantitative research methods Implications for Software Engineering Education
ALOHA AND MAHALO!!